-
7
-
-
3142725535
-
Semi-supervised learning on riemannian manifolds
-
Mikhail Belkin and Partha Niyogi. Semi-supervised learning on riemannian manifolds. Machine Learning, 56:209-239, 2003.
-
(2003)
Machine Learning
, vol.56
, pp. 209-239
-
-
Belkin, M.1
Niyogi, P.2
-
8
-
-
31844446899
-
Manifold regularization: A geometric framework for learning from examples
-
Technical Report TR-2004-06, University of Chicago
-
Mikhail Belkin, Partha Niyogi, and Vikas Sindhwani. Manifold regularization: A geometric framework for learning from examples. Technical Report TR-2004-06, University of Chicago, 2004.
-
(2004)
-
-
Belkin, M.1
Niyogi, P.2
Sindhwani, V.3
-
9
-
-
4344635655
-
Out-of-sample extensions for LLE, Isomap, MDS, eigenmaps and spectral clustering
-
Yoshua Bengio, Jean-Francois Paiement, Pascal Vincent, Olivier Delalleau, Nicolas Le Roux, and Marie Ouimet. Out-of-sample extensions for LLE, Isomap, MDS, eigenmaps and spectral clustering. In Neural Information Processing Systems, 2003.
-
(2003)
Neural Information Processing Systems
-
-
Bengio, Y.1
Paiement, J.2
Vincent, P.3
Delalleau, O.4
Roux, N.L.5
Ouimet, M.6
-
11
-
-
11744378648
-
Atomic decomposition by basis pursuit
-
Technical Report 479, Stanford University Department of Statistics
-
Scott Shaobing Chen, David L. Donoho, and Michael A. Saunders. Atomic decomposition by basis pursuit. Technical Report 479, Stanford University Department of Statistics, 1995.
-
(1995)
-
-
Shaobing Chen, S.1
Donoho, D.L.2
Saunders, M.A.3
-
12
-
-
34249753618
-
Support vector networks
-
Corinna Cortes and Vladimir Vapnik. Support vector networks. Machine Learning, 20:1-25, 1995.
-
(1995)
Machine Learning
, vol.20
, pp. 1-25
-
-
Cortes, C.1
Vapnik, V.2
-
15
-
-
0034419669
-
Regularization networks and support vector machines
-
Theodoras Evgeniou, Massimiliano Pontil, and Tomaso Poggio. Regularization networks and support vector machines. Advances In Computational Mathematics, 13(1):1-50, 2000.
-
(2000)
Advances In Computational Mathematics
, vol.13
, Issue.1
, pp. 1-50
-
-
Evgeniou, T.1
Pontil, M.2
Poggio, T.3
-
16
-
-
0000249788
-
An equivalence between sparse approximation and support vecto machines
-
Federico Girosi. An equivalence between sparse approximation and support vecto machines. Neural Computation, 10:1455-1480, 1998.
-
(1998)
Neural Computation
, vol.10
, pp. 1455-1480
-
-
Girosi, F.1
-
18
-
-
8844278523
-
Learning the kernel matrix with semidefinite programming
-
Gert R. G. Lanckriet, Nello Cristianini, Peter Bartlett, Laurent El Ghaoui, and Michael I. Jordan. Learning the kernel matrix with semidefinite programming. Journal of Machine Learning Research, 5:24-72, 2004.
-
(2004)
Journal of Machine Learning Research
, vol.5
, pp. 24-72
-
-
Lanckriet, G.R.G.1
Cristianini, N.2
Bartlett, P.3
Ghaoui, L.E.4
Jordan, M.I.5
-
20
-
-
34250122797
-
Interpolation of scattered data: Distance matrices and conditionally positive functions
-
Charles A. Micchelli. Interpolation of scattered data: distance matrices and conditionally positive functions. Constructive Approximation, 2(1):11-22, 1986.
-
(1986)
Constructive Approximation
, vol.2
, Issue.1
, pp. 11-22
-
-
Micchelli, C.A.1
-
21
-
-
0025490985
-
Networks for approximation and learning
-
September
-
Tomaso Poggio and Federico Girosi. Networks for approximation and learning. Proceedings of the IEEE, 78(9): 1481-1497, September 1990.
-
(1990)
Proceedings of the IEEE
, vol.78
, Issue.9
, pp. 1481-1497
-
-
Poggio, T.1
Girosi, F.2
-
22
-
-
33947288303
-
-
b
-
Tomaso Poggio, Sayan Mukherjee, Ryan M. Rifkin, Alex Rakhlin, and Alessandro Verri. b. In Proceedings of the Conference on Uncertainty in Geometric Computations, 2001.
-
(2001)
Proceedings of the Conference on Uncertainty in Geometric Computations
-
-
Poggio, T.1
Mukherjee, S.2
Rifkin, R.M.3
Rakhlin, A.4
Verri, A.5
-
25
-
-
33947235414
-
-
Unpublished phd thesis
-
Ben Recht. Unpublished phd thesis. 2006.
-
(2006)
-
-
Recht, B.1
-
30
-
-
0037695279
-
-
World Scientific
-
Johan A. K. Suykens, Tony Van Gestel, Jos De Brabanter, Bart De Moor, and Joos Vandewalle. Least Squares Support Vector Machines. World Scientific, 2002.
-
(2002)
Least Squares Support Vector Machines
-
-
Suykens, J.A.K.1
Van Gestel, T.2
Brabanter, J.D.3
Moor, B.D.4
Vandewalle, J.5
-
33
-
-
0003241881
-
Spline Models for Observational Data
-
of, Society for Industrial & Applied Mathematics
-
Grace Wahba. Spline Models for Observational Data, volume 59 of CBMS-NSF Regional Conference Series in Applied Mathematics. Society for Industrial & Applied Mathematics, 1990.
-
(1990)
CBMS-NSF Regional Conference Series in Applied Mathematics
, vol.59
-
-
Wahba, G.1
-
35
-
-
33947281307
-
-
Ji Zhu, Saharon Rosset, Trevor Hastie, and Rob Tibshirani. 1-norm support vector machines. In Neural Information Processing Systems, 2003.
-
Ji Zhu, Saharon Rosset, Trevor Hastie, and Rob Tibshirani. 1-norm support vector machines. In Neural Information Processing Systems, 2003.
-
-
-
|